A Destination Earth Platform use case.
Documentation can be viewed at https://destination-earth.github.io/DestinE_ESA_GFTS.
To get a local copy of the GFTS repository, you can clone it on your local computer and/or server:
git clone https://github.com/destination-earth/DestinE_ESA_GFTS.git
Jupyter notebooks to showcase GFTS are in the docs folder and can be run after installing Python and the required packages listed in the .binder/environment.yml file.
To install Python, we recommend to install conda or miniconda and then create a new conda environment using .binder/environment.yml:
conda env create -f environment.yml
Do not forget to switch to the gfts conda environment prior to executing any Jupyter notebooks or programs from the GFTS repository.
conda activate gfts
To deactivate the gfts environment:
conda deactivate
Once all the required packages are installed, you can start JupyterLab and run the jupyter notebooks from the docs folder:
jupyter lab
Before building the GFTS docker image, you would need to install docker.
Make sure you change directory to gfts-track-reconstruction/jupyterhub/images/user before executing the command below:
docker build -t gfts:latest .
docker run -p 7777:8888 -i -t gfts:latest jupyter lab --ip=0.0.0.0 --no-browser
Open your web browser and enter the following command:
http://127.0.0.1:7777/lab
Then you need to enter your token: it can be found at the bottom of the printout you got after running the docker run command given above.
Instructions on how to build and deploy GFTS hub are described in ./gfts-track-reconstruction/jupyterhub/README.md.
The current Jupyterhub deployment is done on OVH cloud operator.
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